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相关概念视频

Controller Configurations01:22

Controller Configurations

149
Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
149
PD Controller: Design01:26

PD Controller: Design

352
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
352
Control Systems01:10

Control Systems

1.4K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
1.4K
Root-Locus Method01:19

Root-Locus Method

213
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
213
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

149
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
149
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

178
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
178

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相关实验视频

Updated: Sep 12, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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多个传感器容错的预测控制,用于自主地表车辆的形成.

Wenxiang Wu1, Chenguang Liu2, Xiumin Chu2

  • 1State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan, 430063, China; School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China.

ISA transactions
|August 7, 2025
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概括

这项研究引入了自主地表车辆 (ASV) 车队的新故障耐受性控制方法,尽管传感器故障,但加强了合作控制. DEKF-MPC方法确保了准确的轨迹跟踪和ASV的航向维护.

关键词:
自主地表车辆的形成分布式扩展卡尔曼过器有故障耐受性的控制器.模型预测控制模型预测控制多个传感器出现故障.沿着路径的路径遵循的路径.

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科学领域:

  • 机器人和控制系统 机器人和控制系统
  • 海洋工程 海洋工程
  • 容错系统 容错系统

背景情况:

  • 自主地表车辆 (ASV) 的合作控制受到多个传感器故障的挑战,影响导航和形成稳定性.
  • 现有的方法在动态和多个传感器退化场景下努力保持强大的形成控制.

研究的目的:

  • 为ASV形成路径在多个传感器故障下提出预测性故障耐受性控制策略.
  • 在传感器异常存在时,提高ASV合作控制系统的可靠性和准确性.

主要方法:

  • 开发一个分布式扩展卡尔曼波器 (DEKF) 状态估计器,集成来自其他ASV的故障检测和辅助数据.
  • 实施一个模型预测控制 (MPC) 控制器,利用DEKF估计的状态来实现稳健的轨迹跟踪.
  • 使用虚拟领袖-追随者结构建立ASV形成路径的模型.

主要成果:

  • 拟议的DEKF-MPC方法在模拟中显示出与APF-MPC和RANSAC-EKF-MPC相比的优越性能.
  • 准确的轨迹跟踪和一致的航向维护是ASVs实现的,即使有多个传感器故障.
  • DEKF状态估计器有效估计了ASV位置,通过水的速度 (STW) 和故障条件下的当前速度.

结论:

  • DEKF-MPC策略提供了一个有效的解决方案,用于对ASV结构的故障耐受性合作控制.
  • 这种方法显著提高了在复杂的海洋环境中运行的ASV系统的稳定性和可靠性,传感器不确定性.